Final Independent Project PDF

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Final project...

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Using the “Independent Project Data” set file supplied above, perform an analysis in StatCrunch for the following using the variable(s) of your choice: Variables: Marital status and physical health. Null Hypothesis: There is no relationship between marital status and physical health. Alternative hypothesis: There is a relationship between marital status and physical health. 1.

Frequency distribution of a variable and bar graph of the same variable

Frequency table results for marital: Count = 950 marital Frequen cy Divorced 273 Married 83 Never 594 married

Relative Percent of Frequency Total 0.28736842 28.736842 0.087368421 8.7368421 0.62526316 62.526316

Frequency table results for marital: Count = 950 marital Frequen cy Divorced 273 Married 83 Never 594 married

Relative Percent of Frequency Total 0.28736842 28.736842 0.087368421 8.7368421 0.62526316 62.526316

Cumulative Cumulative Percent of Frequency Total 273 28.736842 356 37.473684 950 100

There were 950 people pooled and asked if they were married, divorced or never married. In those 950 people; 28.73% of them were divorced, 8.74% were married and 62.53% were never married. A frequency distribution table shows the values and how often they occur to easily see patterns in the population.

This graph shows that people who were never married had higher physical health scores than divorced subjects and divorced subjects had higher physical health scores than their married counterparts. This shows that when you are married, your physical health tends to decrease.

Descriptives of a continuous variable: mean, median, mode, skewness, kurtosis, standard deviation and graph of that variable Mean: The average of all the value in the population. Median: The middle number in a list of numbers. Mode: The number that appears the most in a list of numbers. Skewness: A measurement of a shift in a curve. Kurtosis: Measurement of probability and values in a curve compared to a normal distribution. Standard deviation: Amount at which data points change and measure of variation and change in set of values. 2.

Column

Mean

Physical Health 44.591158

MedianMode Skewness

Kurtosis

Std. dev.

47.1 56.6 -0.65590536 -0.51280359 10.890553

istics of the population resulting in a unimodal, leptokurtic, positive skew to the left. This study shows the mean of physical health being 44.59, which exhibits that the most of population has a physical score close to 44.59.

3. Cross tabulation of two variables with the appropriate statistical test Null hypothesis: Marital status and poverty are related. Alternative hypothesis: Marital status and poverty are not related. This study has multiple variables, so cross tabulation is used to see if there is a similarity across the populations. The tabled value of the Chi-Square at degrees of freedom 2 is 5.99. The result from this study shows that the Chi-Square value is 10.266594, which is larger than the tabled value. The hypothesis is rejected which also correlates to the p-value of 0.0059 which is smaller than alpha 0.05, so the hypothesis that poverty and marital status is related is rejected.

Contingency table results: Rows: poverty Columns: marital Cell format Count (Row percent) (Column percent) (Percent of total) (Expected count)

Poverty Status Below poverty Count % within Poverty Status % within Marital Status % of Total Expected Count Above poverty Count % within Poverty Status % within Marital Status % of Total Expected Count Total Count % within Poverty Status % within Marital Status % of Total

Marital Status Divorced Married Never married Total 208 53 472 733 (28.38%) (7.23%) (64.39%) (100%) (76.19%) (63.86%) (79.46%) (77.16%) (21.89%) (5.58%) (49.68%) (77.16%) (210.64) (64.04) (458.32) 65 30 (29.95%) (13.82%) (23.81%) (36.14%) (6.84%) (3.16%) (62.36) (18.96) 273 83 (28.74%) (8.74%) (100%) (100%) (28.74%) (8.74%)

122 217 (56.22%) (100%) (20.54%) (22.84%) (12.84%) (22.84%) (135.68) 594 950 (62.53%) (100%) (100%) (100%) (62.53%) (100%)

Chi-Square test: Statistic DF Value P-value Chi-square 2 10.266594 0.0059 N0: Poverty and marital status are not related. NA: Poverty and marital status are related. P-value is 0.0059 which is less than 0.05, so this is a significant result. Critical tabled Chi-Square at 2 degrees of freedom value is 5.99 which is less than compared to the Chi-Square calculated value of 10.27. This means we can reject the null hypothesis and accept the alternative hypothesis that poverty status and marriage status are related.

4.

Comparison of two groups (single variable) on a single continuous variable with the appropriate statistical test Age and Weight

A two-sample T test was used for this study to test the difference of these populations. The null hypothesis is that there is no difference between age and weight in married people. The alternative hypothesis is that there is a difference between age and weight. The p-value is less than 0.05, so we reject the null hypothesis that there is no difference between age and weight in married people.

Two sample T hypothesis test: μ1 : Mean of age μ2 : Mean of Weight

μ1 - μ2 : Difference between two means H 0 : μ1 - μ2 = 0 H A : μ1 - μ2 ≠ 0 (with pooled variances) Hypothesis test results: Differe Sample Std. DF T-Stat Pnce Diff. Err. value μ 1 - μ2

-136.68 1.5339 18 -...